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Journal of Applied Remote Sensing • Open Access

Sharpening method of satellite thermal image based on the geographical statistical model
Author(s): Pengcheng Qi; Shixiong Hu; Haijun Zhang; Guangmeng Guo

Paper Abstract

To improve the effectiveness of thermal sharpening in mountainous regions, paying more attention to the laws of land surface energy balance, a thermal sharpening method based on the geographical statistical model (GSM) is proposed. Explanatory variables were selected from the processes of land surface energy budget and thermal infrared electromagnetic radiation transmission, then high spatial resolution (57 m) raster layers were generated for these variables through spatially simulating or using other raster data as proxies. Based on this, the local adaptation statistical relationship between brightness temperature (BT) and the explanatory variables, i.e., the GSM, was built at 1026-m resolution using the method of multivariate adaptive regression splines. Finally, the GSM was applied to the high-resolution (57-m) explanatory variables; thus, the high-resolution (57-m) BT image was obtained. This method produced a sharpening result with low error and good visual effect. The method can avoid the blind choice of explanatory variables and remove the dependence on synchronous imagery at visible and near-infrared bands. The influences of the explanatory variable combination, sampling method, and the residual error correction on sharpening results were analyzed deliberately, and their influence mechanisms are reported herein.

Paper Details

Date Published: 12 May 2016
PDF: 17 pages
J. Appl. Remote Sens. 10(2) 025013 doi: 10.1117/1.JRS.10.025013
Published in: Journal of Applied Remote Sensing Volume 10, Issue 2
Show Author Affiliations
Pengcheng Qi, Nanyang Normal Univ. (China)
Henan Univ. (China)
Shixiong Hu, Henan Univ. (China)
East Stroudsburg Univ. (United States)
Haijun Zhang, Nanyang Normal Univ. (China)
Guangmeng Guo, Nanyang Normal Univ. (China)


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